Wireless Sensor Networks (WSNs) have become a key technology for ubiquitous computing environments. In WSNs, battery recharge or replacement is impossible because sensors are left unattended after deployment. Therefore, WSNs need a networking protocol scheme to increase the life time of sensor nodes. The clustering technique is an efficient approach for reducing energy consumption in wireless sensor networks. In cluster topology, however, there is a problem which causes a large amount of energy consumption of cluster head. In addition, in the sparsely deployed sensor field, mesh topology can be more energy-efficient than cluster topology. In this paper, we propose a Hybrid Cluster Mesh (HCM) scheme, which recognizes the density of neighbor nodes and each node decides its topology itself, and HCM-RO (reorganization) scheme which reorganizes clusters. Simulation results show that the proposed hybrid topology control scheme is more energy-efficient than each topology of cluster or mesh.

Energy-efficient operations are essential to prolonging the lifetime of wireless sensor networks. Clustering sensor nodes is one approach that can reduce energy consumption by aggregating data, controlling transmission power levels, and putting redundant sensor nodes to sleep. To distribute the role of a cluster head, clustering approaches should be based on efficient cluster configuration schemes. Therefore, low overhead in the cluster configuration process is one of the key constraints for energy-efficient clustering. In this paper, we present an autonomous clustering approach using a coverage estimation-based self-pruning algorithm. Our strategy for clustering is to allow the best candidate node within its own cluster range to declare itself as a cluster head and to dominate the other nodes in the range. This same self-declaration strategy is also used in the active sensor election process. As a result, the proposed scheme can minimize clustering overheads by obviating both the requirements of collecting neighbor information beforehand and the iterative negotiating steps of electing cluster heads. The proposed scheme allows any type of sensor network application, including spatial query execution or periodic environment monitoring, to operate in an energy-efficient manner.